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Discovering Engagement Personas in a Digital Diabetes Prevention Program
Digital health technologies are shaping the future of preventive health care. We present a quantitative approach for discovering and characterizing engagement personas: longitudinal engagement patterns in a fully digital diabetes prevention program. We used a two-step approach to discovering engagem...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9220103/ https://www.ncbi.nlm.nih.gov/pubmed/35735369 http://dx.doi.org/10.3390/bs12060159 |
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author | Hori, Jonathan H. Sia, Elizabeth X. Lockwood, Kimberly G. Auster-Gussman, Lisa A. Rapoport, Sharon Branch, OraLee H. Graham, Sarah A. |
author_facet | Hori, Jonathan H. Sia, Elizabeth X. Lockwood, Kimberly G. Auster-Gussman, Lisa A. Rapoport, Sharon Branch, OraLee H. Graham, Sarah A. |
author_sort | Hori, Jonathan H. |
collection | PubMed |
description | Digital health technologies are shaping the future of preventive health care. We present a quantitative approach for discovering and characterizing engagement personas: longitudinal engagement patterns in a fully digital diabetes prevention program. We used a two-step approach to discovering engagement personas among n = 1613 users: (1) A univariate clustering method using two unsupervised k-means clustering algorithms on app- and program-feature use separately and (2) A bivariate clustering method that involved comparing cluster labels for each member across app- and program-feature univariate clusters. The univariate analyses revealed five app-feature clusters and four program-feature clusters. The bivariate analysis revealed five unique combinations of these clusters, called engagement personas, which represented 76% of users. These engagement personas differed in both member demographics and weight loss. Exploring engagement personas is beneficial to inform strategies for personalizing the program experience and optimizing engagement in a variety of digital health interventions. |
format | Online Article Text |
id | pubmed-9220103 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-92201032022-06-24 Discovering Engagement Personas in a Digital Diabetes Prevention Program Hori, Jonathan H. Sia, Elizabeth X. Lockwood, Kimberly G. Auster-Gussman, Lisa A. Rapoport, Sharon Branch, OraLee H. Graham, Sarah A. Behav Sci (Basel) Article Digital health technologies are shaping the future of preventive health care. We present a quantitative approach for discovering and characterizing engagement personas: longitudinal engagement patterns in a fully digital diabetes prevention program. We used a two-step approach to discovering engagement personas among n = 1613 users: (1) A univariate clustering method using two unsupervised k-means clustering algorithms on app- and program-feature use separately and (2) A bivariate clustering method that involved comparing cluster labels for each member across app- and program-feature univariate clusters. The univariate analyses revealed five app-feature clusters and four program-feature clusters. The bivariate analysis revealed five unique combinations of these clusters, called engagement personas, which represented 76% of users. These engagement personas differed in both member demographics and weight loss. Exploring engagement personas is beneficial to inform strategies for personalizing the program experience and optimizing engagement in a variety of digital health interventions. MDPI 2022-05-24 /pmc/articles/PMC9220103/ /pubmed/35735369 http://dx.doi.org/10.3390/bs12060159 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Hori, Jonathan H. Sia, Elizabeth X. Lockwood, Kimberly G. Auster-Gussman, Lisa A. Rapoport, Sharon Branch, OraLee H. Graham, Sarah A. Discovering Engagement Personas in a Digital Diabetes Prevention Program |
title | Discovering Engagement Personas in a Digital Diabetes Prevention Program |
title_full | Discovering Engagement Personas in a Digital Diabetes Prevention Program |
title_fullStr | Discovering Engagement Personas in a Digital Diabetes Prevention Program |
title_full_unstemmed | Discovering Engagement Personas in a Digital Diabetes Prevention Program |
title_short | Discovering Engagement Personas in a Digital Diabetes Prevention Program |
title_sort | discovering engagement personas in a digital diabetes prevention program |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9220103/ https://www.ncbi.nlm.nih.gov/pubmed/35735369 http://dx.doi.org/10.3390/bs12060159 |
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